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Wind farm power curve modeling using adaptive neuro-fuzzy inference systems


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Johnson, PL and Negnevitsky, M (2007) Wind farm power curve modeling using adaptive neuro-fuzzy inference systems. In: the 8th international conference on intelligent technologies, 12-14 Dec 2007, Sydney, Australia.

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Abstract—Wind power is an important renewable energy source which is currently experiencing rapid global growth. As the penetration of wind power into electricity grids increases, the need for accurate modeling and forecasting of this inherently variable source of power becomes essential. In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) approach to wind farm power curve modeling is presented. Results from a case study demonstrate the advantages of defining fuzzy inference system parameters using intuitive IF-THEN rules and initial membership function allocations compared to a purely “black box” ANFIS modeling approach.

Item Type: Conference or Workshop Item (Paper)
Keywords: wind power; wind farm power curve; Adaptive Neuro-Fuzzy Inference System (ANFIS)
Page Range: pp. 168-175
Additional Information:

Copyright © 2007, Eighth International Conference on Intelligent Technologies (InTech 2007). All Rights Reserved

Date Deposited: 07 Apr 2008 14:58
Last Modified: 18 Nov 2014 03:36
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